{"cells":[{"cell_type":"markdown","metadata":{"id":"qEDuDC-wD5xj"},"source":["#How well can Multimodal LLMs interpret complex financial data? Let’s find out!\n","\n","▶ I recently conducted an experiment with 5 different Multimodal LLMs, and sizes, to see how they handle interpreting a complex financial chart. The models tested were: Llama-3.2-11B-Vision, Pixtral-12B, Qwen 2 VL 2B, and the heavyweights: Claude 3.5 Sonnet and GPT-4o.\n","\n","▶ The chart I used was taken from JP Morgan's 2022 report, featuring multiple data types and visual elements like bar and line graphs—a real test of the models' ability to process intricate financial information.\n","\n","▶ Why does this matter? In finance, being able to accurately interpret visuals and numerical data is critical. I wanted to assess:\n","\n","*   How well these models handle mixed data formats.\n","*   Whether they can interpret complex financial values.\n","*   How feasible it is to use them in real-world financial analysis, despite varying model sizes and architectures.\n","\n","▶ Even though these models differ in size and complexity, the ultimate goal was to determine their potential when working with numbers and visual data. Some fascinating insights emerged!\n","\n","▶ How I run them?\n","\n","*   I have run a quantized version of Llama-3.2-11B-Vision, on Google colab, using GPU (Runtime ==> Change Runtime Type ==> GPU)\n","\n","*   I used MistralAI for Pixtral-12B (Mistral AI Key + subscribe to free usage)\n","\n","*   I used HuggingFace for Qwen2VL\n","\n","*   I used OpenAI and Anthropic API for GPT-4o and Claude 3.5 Sonnet  \n","\n","\n","▶ Key Takeaways:\n","\n","*   Well, the largest models excel in extracting the correct numbers from this complex chart. However, they sometimes do not extract the whole expected values (For example, they ommit to extract the first table, or they don't capture the whole years from the chart...)\n","\n","*   The smallest models, while they can capture all the metrics included in the chart, they don't extract yet the accurate numbers...I believe they are good at describing images, but not yet for exact numbers."]},{"cell_type":"markdown","source":["Here is the image from which we want multimodal LLMs to extract numbers:"],"metadata":{"id":"CWAA4ch-DCiD"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":703},"executionInfo":{"elapsed":4648,"status":"ok","timestamp":1727983240525,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"h212Nnfz9GLi","outputId":"f65ed371-efd5-4f4d-8d12-313a6d318201"},"outputs":[{"output_type":"execute_result","data":{"image/png":"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\n","text/plain":["<IPython.core.display.Image object>"]},"metadata":{},"execution_count":5}],"source":["# path_img = local_path\n","from IPython.display import Image\n","Image(path_img)"]},{"cell_type":"markdown","source":["# Install Libs"],"metadata":{"id":"miHsR4imzlud"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":4196,"status":"ok","timestamp":1727945616320,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"KkoXj8wU8rVe","outputId":"c58e05f0-01fa-418c-d7ea-a7f635f208cf"},"outputs":[{"name":"stdout","output_type":"stream","text":["\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/295.8 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m295.8/295.8 kB\u001b[0m \u001b[31m10.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h"]}],"source":["# !pip install anthropic -q\n","# !pip install openai -q"]},{"cell_type":"markdown","metadata":{"id":"2rEcA_sUDrdE"},"source":["# Specify Keys"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"mSlvkQxD8_DA"},"outputs":[],"source":["from google.colab import userdata\n","CLAUDE_API_KEY = userdata.get('CLAUDE_API_KEY')\n","OPENAI_API_KEY = userdata.get('OPENAI_API_KEY')\n","MISTRAL_API_KEY = userdata.get('MISTRAL_API_KEY')\n","\n","import openai\n","openai.api_key = OPENAI_API_KEY\n","\n","import anthropic"]},{"cell_type":"markdown","metadata":{"id":"a4RQaQcpDovI"},"source":["# Load Image"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"CKsPJFXd-XUf"},"outputs":[],"source":["import io\n","import base64\n","from PIL import Image\n","\n","# Convert the PNG images to base64 encoded strings: One example images\n","images = [Image.open(f\"{path_img}\")]\n","\n","base64_encoded_pngs = []\n","quality=75\n","max_size=(1024, 1024)\n","for image in images:\n","        # Resize the image if it exceeds the maximum size\n","        if image.size[0] > max_size[0] or image.size[1] > max_size[1]:\n","            image.thumbnail(max_size, Image.Resampling.LANCZOS)\n","        image_data = io.BytesIO()\n","        image.save(image_data, format='PNG', optimize=True, quality=quality)\n","        image_data.seek(0)\n","        base64_encoded = base64.b64encode(image_data.getvalue()).decode('utf-8')\n","        base64_encoded_pngs.append(base64_encoded)"]},{"cell_type":"markdown","metadata":{"id":"WC9wQoEaDW_1"},"source":["# GPT-4o"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"-bLvPL1B-cE4"},"outputs":[],"source":["from openai import OpenAI\n","\n","client_openai = OpenAI(api_key=OPENAI_API_KEY)\n","MODEL_NAME_GPT = \"gpt-4o-mini\"\n","\n","def get_completion_gpt4o(messages, model_name):\n","    response = client_openai.chat.completions.create(\n","        model=model_name,\n","        # max_tokens=2048,\n","        temperature=0,\n","        messages=messages\n","    )\n","    print(response.model)\n","    return response.choices[0].message.content\n","\n","def append_message(content, question):\n","    content.append({\"type\": \"text\", \"text\": question})\n","    messages = [\n","      {\n","          \"role\": 'user',\n","          \"content\": content\n","      }\n","    ]\n","    return messages"]},{"cell_type":"markdown","metadata":{"id":"zanG-_rw2mqO"},"source":["## Prompt 1: raw data without explicit format"]},{"cell_type":"markdown","metadata":{"id":"KAvz9oJo2tlp"},"source":["🔽 ⬇ : It didn't to extract the first table: 🔽 ⬇"]},{"cell_type":"markdown","metadata":{"id":"xS66tIMp63FU"},"source":["The extracted data is good"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"AEM9j5Au-lCq"},"outputs":[],"source":["content = [{\"type\": \"image_url\", \"image_url\": {\"url\": f\"data:image/png;base64,{encoded_png}\"}} for encoded_png in base64_encoded_pngs]\n","question = \"Extract raw data from the image.\"\n","messages_gpt = append_message(content, question)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":7484,"status":"ok","timestamp":1727949694686,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"v2p683cQ08PX","outputId":"1f5ec622-26c3-4397-e1d7-7cb1d62253a8"},"outputs":[{"name":"stdout","output_type":"stream","text":["gpt-4o-2024-08-06\n","Here is the extracted data from the image:\n","\n","### Net Income ($B)\n","- 2004: $4.5\n","- 2005: $8.5\n","- 2006: $14.4\n","- 2007: $15.4\n","- 2008: $5.6\n","- 2009: $11.7\n","- 2010: $17.4\n","- 2011: $19.0\n","- 2012: $21.3\n","- 2013: $17.9\n","- 2014: $21.7\n","- 2015: $24.4\n","- 2016: $24.7\n","- 2017: $24.4\n","- 2018: $32.5\n","- 2019: $36.4\n","- 2020: $29.1\n","- 2021: $48.3\n","- 2022: $37.7\n","\n","### Diluted Earnings Per Share (EPS)\n","- 2004: $1.52\n","- 2005: $2.35\n","- 2006: $4.00\n","- 2007: $4.33\n","- 2008: $1.35\n","- 2009: $2.26\n","- 2010: $3.96\n","- 2011: $4.48\n","- 2012: $5.20\n","- 2013: $4.34\n","- 2014: $5.29\n","- 2015: $6.00\n","- 2016: $6.19\n","- 2017: $6.31\n","- 2018: $9.00\n","- 2019: $10.72\n","- 2020: $8.88\n","- 2021: $15.36\n","- 2022: $12.09\n","\n","### Return on Tangible Common Equity (ROTCE)\n","- 2004: 10%\n","- 2005: 15%\n","- 2006: 24%\n","- 2007: 22%\n","- 2008: 6%\n","- 2009: 10%\n","- 2010: 15%\n","- 2011: 15%\n","- 2012: 15%\n","- 2013: 11%\n","- 2014: 13%\n","- 2015: 13%\n","- 2016: 12%\n","- 2017: 13%\n","- 2018: 17%\n","- 2019: 19%\n","- 2020: 14%\n","- 2021: 23%\n","- 2022: 18%\n","\n","### Additional Notes\n","- Adjusted net income for 2017 excludes $2.4 billion due to the Tax Cuts and Jobs Act.\n","- ROTCE excluding reserve release/build was 19.3% for 2020 and 18.5% for 2021.\n","CPU times: user 46.8 ms, sys: 1.86 ms, total: 48.7 ms\n","Wall time: 7.21 s\n"]}],"source":["%%time\n","MODEL_NAME_GPT = \"gpt-4o\"\n","print(get_completion_gpt4o(messages_gpt, MODEL_NAME_GPT))"]},{"cell_type":"markdown","metadata":{"id":"hJG8vJ252hVn"},"source":["## Prompt: Json format"]},{"cell_type":"markdown","metadata":{"id":"3o-m6lgn3SOd"},"source":["🔽 ⬇ All data are extracted :🔽 ⬇"]},{"cell_type":"markdown","metadata":{"id":"xY2UTeye3Wjv"},"source":["✅ Numbers coming from the chart are **GOOD** ✅"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":6657,"status":"ok","timestamp":1727949932252,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"6oYbYNA-1tB-","outputId":"721519d9-053c-4cb0-b603-969936476e2f"},"outputs":[{"name":"stdout","output_type":"stream","text":["gpt-4o-2024-08-06\n","```json\n","{\n","  \"years\": [\n","    2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022\n","  ],\n","  \"net_income\": [\n","    4.5, 8.5, 14.4, 15.4, 5.6, 11.7, 17.4, 19.0, 21.3, 21.7, 17.9, 21.8, 24.4, 24.7, 32.5, 36.4, 29.1, 48.3, 37.7\n","  ],\n","  \"diluted_eps\": [\n","    1.52, 2.35, 4.00, 4.33, 1.35, 2.26, 3.96, 4.48, 5.20, 5.29, 4.34, 5.29, 6.00, 6.19, 9.00, 10.72, 8.88, 15.36, 12.09\n","  ],\n","  \"rotce\": [\n","    10, 15, 24, 22, 6, 10, 15, 15, 15, 15, 13, 13, 12, 13, 17, 19, 14, 23, 18\n","  ],\n","  \"reported\": {\n","    \"2020\": {\n","      \"net_income\": 29.1,\n","      \"diluted_eps\": 8.88,\n","      \"rotce\": 14.4\n","    },\n","    \"2021\": {\n","      \"net_income\": 48.3,\n","      \"diluted_eps\": 15.36,\n","      \"rotce\": 23.0\n","    },\n","    \"2022\": {\n","      \"net_income\": 37.7,\n","      \"diluted_eps\": 12.09,\n","      \"rotce\": 17.9\n","    }\n","  },\n","  \"excluding_reserve_release_build\": {\n","    \"2020\": {\n","      \"net_income\": 38.4,\n","      \"diluted_eps\": 11.87,\n","      \"rotce\": 19.3\n","    },\n","    \"2021\": {\n","      \"net_income\": 33.1,\n","      \"diluted_eps\": 12.35,\n","      \"rotce\": 18.5\n","    },\n","    \"2022\": {\n","      \"net_income\": 40.4,\n","      \"diluted_eps\": 12.99,\n","      \"rotce\": 19.1\n","    }\n","  },\n","  \"notes\": {\n","    \"1\": \"Firmwide results excluding reserve release/build are non-GAAP financial measures.\",\n","    \"2\": \"Adjusted net income excludes $2.4 billion from net income in 2017 as a result of the enactment of the Tax Cuts and Jobs Act.\",\n","    \"GAAP\": \"Generally accepted accounting principles\",\n","    \"ROTCE\": \"Return on tangible common equity\"\n","  }\n","}\n","```\n"]}],"source":["content = [{\"type\": \"image_url\", \"image_url\": {\"url\": f\"data:image/jpeg;base64,{encoded_png}\"}} for encoded_png in base64_encoded_pngs]\n","question = \"Extract ALL raw data from the image in a json format.\"\n","messages_gpt = append_message(content, question)\n","# MODEL_NAME_GPT = \"gpt-4o\"\n","print(get_completion_gpt4o(messages_gpt, MODEL_NAME_GPT))"]},{"cell_type":"markdown","metadata":{"id":"Le7s4ioi35c9"},"source":["One values that are not correct from the first table:\n","\n","\"2021\": ==> \"net_income\": 33.1,"]},{"cell_type":"markdown","source":["## Prompt: Markdown format"],"metadata":{"id":"u8cc0DsY-V-0"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"tF_cLnT-rX4c"},"outputs":[],"source":["content = [{\"type\": \"image_url\", \"image_url\": {\"url\": f\"data:image/jpeg;base64,{encoded_png}\"}} for encoded_png in base64_encoded_pngs]\n","question = \"Extract raw data from the image in a markdown format when it's possible.\"\n","messages_gpt = append_message(content, question)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":6216,"status":"ok","timestamp":1727947112786,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"9eNAOCFarGTl","outputId":"1c555918-839d-4970-8237-b85670320c75"},"outputs":[{"name":"stdout","output_type":"stream","text":["gpt-4o-2024-08-06\n","```markdown\n","| Year | Net Income ($B) | Diluted EPS ($) | ROTCE (%) | Net Income Excluding Reserve Release/Build ($B) | Diluted EPS Excluding Reserve Release/Build ($) | ROTCE Excluding Reserve Release/Build (%) |\n","|------|-----------------|-----------------|-----------|-----------------------------------------------|-----------------------------------------------|------------------------------------------|\n","| 2004 | $4.5            | $1.52           | 10%       |                                               |                                               |                                          |\n","| 2005 | $8.5            | $2.35           | 15%       |                                               |                                               |                                          |\n","| 2006 | $14.4           | $4.00           | 24%       |                                               |                                               |                                          |\n","| 2007 | $15.4           | $4.33           | 22%       |                                               |                                               |                                          |\n","| 2008 | $5.6            | $1.35           | 6%        |                                               |                                               |                                          |\n","| 2009 | $11.7           | $2.26           | 10%       |                                               |                                               |                                          |\n","| 2010 | $17.4           | $3.96           | 15%       |                                               |                                               |                                          |\n","| 2011 | $19.0           | $4.48           | 15%       |                                               |                                               |                                          |\n","| 2012 | $21.3           | $5.19           | 15%       |                                               |                                               |                                          |\n","| 2013 | $17.9           | $4.34           | 11%       |                                               |                                               |                                          |\n","| 2014 | $21.7           | $5.29           | 15%       |                                               |                                               |                                          |\n","| 2015 | $24.4           | $6.00           | 13%       |                                               |                                               |                                          |\n","| 2016 | $24.7           | $6.19           | 13%       |                                               |                                               |                                          |\n","| 2017 | $24.4           | $6.31           | 12%       | Adjusted ROTCE: 13.6%                         |                                               |                                          |\n","| 2018 | $32.5           | $9.00           | 17%       |                                               |                                               |                                          |\n","| 2019 | $36.4           | $10.72          | 19%       |                                               |                                               |                                          |\n","| 2020 | $29.1           | $8.88           | 14.4%     | $38.4                                         | $11.87                                        | 19.3%                                    |\n","| 2021 | $48.3           | $15.36          | 23.0%     | $33.1                                         | $12.35                                        | 18.5%                                    |\n","| 2022 | $37.7           | $12.09          | 17.9%     | $40.4                                         | $12.99                                        | 19.1%                                    |\n","```\n","\n","CPU times: user 32 ms, sys: 3.48 ms, total: 35.5 ms\n","Wall time: 5.96 s\n"]}],"source":["%%time\n","MODEL_NAME_GPT = \"gpt-4o\"\n","print(get_completion_gpt4o(messages_gpt, MODEL_NAME_GPT))"]},{"cell_type":"markdown","metadata":{"id":"bGmR5Gd4rhwE"},"source":["# GPT-4o-mini"]},{"cell_type":"markdown","metadata":{"id":"teRjxX24rkxM"},"source":["Not good: It extracted some of the data (from the chart) but the values are not good"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":13407,"status":"ok","timestamp":1727946855284,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"L-UibB-eqFMt","outputId":"a5d57845-7c68-4389-91db-b8fd25f1ed3d"},"outputs":[{"name":"stdout","output_type":"stream","text":["gpt-4o-mini-2024-07-18\n","Here is the raw data extracted from the image:\n","\n","### Net Income ($ in billions)\n","- 2004: $2.35\n","- 2005: $14.4\n","- 2006: $17.4\n","- 2007: $21.3\n","- 2008: $11.7\n","- 2009: $5.1\n","- 2010: $4.4\n","- 2011: $4.3\n","- 2012: $4.8\n","- 2013: $21.7\n","- 2014: $24.4\n","- 2015: $24.7\n","- 2016: $26.9\n","- 2017: $9.00\n","- 2018: $26.9\n","- 2019: $10.72\n","- 2020: $29.1\n","- 2021: $48.3\n","- 2022: $37.7\n","\n","### Diluted EPS ($)\n","- 2004: $1.52\n","- 2005: $8.5\n","- 2006: $14.4\n","- 2007: $15.4\n","- 2008: $11.7\n","- 2009: $1.35\n","- 2010: $2.26\n","- 2011: $4.34\n","- 2012: $4.8\n","- 2013: $12.35\n","- 2014: $12.99\n","- 2015: $12.09\n","- 2016: $6.19\n","- 2017: $6.31\n","- 2018: $8.88\n","- 2019: $8.88\n","- 2020: $8.88\n","- 2021: $15.36\n","- 2022: $12.09\n","\n","### ROTCE (%)\n","- 2004: 10%\n","- 2005: 15%\n","- 2006: 24%\n","- 2007: 22%\n","- 2008: 10%\n","- 2009: 6%\n","- 2010: 15%\n","- 2011: 15%\n","- 2012: 13%\n","- 2013: 19%\n","- 2014: 21%\n","- 2015: 17%\n","- 2016: 12%\n","- 2017: 13.6% (adjusted)\n","- 2018: 17%\n","- 2019: 14%\n","- 2020: 14.4%\n","- 2021: 23%\n","- 2022: 18% \n","\n","### Additional Notes\n","- Adjusted net income excludes a $2.4 billion net income in 2017 due to the Tax Cuts and Jobs Act.\n","- ROTCE excluding reserve release/build was 19.3% for 2020 and 18.5% for 2021.\n","CPU times: user 53.3 ms, sys: 6.71 ms, total: 60 ms\n","Wall time: 13.1 s\n"]}],"source":["%%time\n","MODEL_NAME_GPT = \"gpt-4o-mini\"\n","print(get_completion_gpt4o(messages_gpt, MODEL_NAME_GPT))"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":9412,"status":"ok","timestamp":1727946706120,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"UOM_2dqCpZlN","outputId":"1326760b-f63e-481d-d62f-2496cf524642"},"outputs":[{"name":"stdout","output_type":"stream","text":["gpt-4o-mini-2024-07-18\n","Here’s the raw data extracted from the chart in a markdown table format:\n","\n","```markdown\n","| Year | Net Income ($B) | Diluted EPS ($) | ROTCE (%) |\n","|------|------------------|------------------|-----------|\n","| 2004 | 2.1              | 2.35             | 10%       |\n","| 2005 | 4.5              | 8.5              | 15%       |\n","| 2006 | 14.4             | 14.4             | 24%       |\n","| 2007 | 15.4             | 11.7             | 22%       |\n","| 2008 | 6.0              | 4.3              | 10%       |\n","| 2009 | 3.6              | 1.35             | 6%        |\n","| 2010 | 4.4              | 2.26             | 12%       |\n","| 2011 | 5.1              | 3.4              | 15%       |\n","| 2012 | 21.3             | 5.19             | 15%       |\n","| 2013 | 21.7             | 4.48             | 15%       |\n","| 2014 | 24.4             | 6.00             | 13%       |\n","| 2015 | 24.7             | 6.19             | 13%       |\n","| 2016 | 24.4             | 6.31             | 12%       |\n","| 2017 | 26.9             | 9.00             | 17%       |\n","| 2018 | 32.5             | 10.72            | 19%       |\n","| 2019 | 29.1             | 8.88             | 14%       |\n","| 2020 | 29.1             | 8.88             | 14.4%     |\n","| 2021 | 48.3             | 15.36            | 23%       |\n","| 2022 | 37.7             | 12.09            | 18%       |\n","```\n","\n","This table summarizes the net income, diluted earnings per share, and return on tangible common equity for the years 2004 to 2022.\n","CPU times: user 41.1 ms, sys: 1.57 ms, total: 42.7 ms\n","Wall time: 9.17 s\n"]}],"source":["%%time\n","#I asked for markdown format\n","MODEL_NAME_GPT = \"gpt-4o-mini\"\n","print(get_completion_gpt4o(messages_gpt, MODEL_NAME_GPT))"]},{"cell_type":"markdown","metadata":{"id":"Xsa3SBWZDTm3"},"source":["# Claude Sonnet 3.5"]},{"cell_type":"markdown","source":["**Very Good results!**"],"metadata":{"id":"ksCNzHpn-0m8"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"yk4FC7oT_Tft"},"outputs":[],"source":["client_claude = anthropic.Anthropic(\n","    api_key=CLAUDE_API_KEY,\n",")\n","\n","MODEL_NAME = \"claude-3-5-sonnet-20240620\"\n","def get_completion_claude(messages):\n","    response = client_claude.messages.create(\n","        model=MODEL_NAME,\n","        max_tokens=2048,\n","        temperature=0,\n","        messages=messages\n","    )\n","    print(response.model)\n","    return response.content[0].text"]},{"cell_type":"markdown","metadata":{"id":"hTe9WV0Vwa5R"},"source":["## Prompt 1"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"d-ufIYDo_bh9"},"outputs":[],"source":["content = [{\"type\": \"image\", \"source\": {\"type\": \"base64\", \"media_type\": \"image/png\", \"data\": encoded_png}} for encoded_png in base64_encoded_pngs]\n","question = \"Extract raw data information from the images.\"\n","messages_claude = append_message(content, question)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":9630,"status":"ok","timestamp":1727947301164,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"SaVMDJCsrzbc","outputId":"c0413be5-383b-489e-efca-99dd0df66fc2"},"outputs":[{"name":"stdout","output_type":"stream","text":["claude-3-5-sonnet-20240620\n","Here's the raw data extracted from the image:\n","\n","Earnings, Diluted Earnings per Share and Return on Tangible Common Equity 2004-2022:\n","\n","Reported data:\n","2020: Net Income ($B): $29.1, Diluted EPS ($): $8.88, ROTCE: 14.4%\n","2021: Net Income ($B): $48.3, Diluted EPS ($): $15.36, ROTCE: 23.0%\n","2022: Net Income ($B): $37.7, Diluted EPS ($): $12.09, ROTCE: 17.7%\n","\n","Excluding reserve release/build:\n","2020: Net Income ($B): $28.4, Diluted EPS ($): $11.67, ROTCE: 19.3%\n","2021: Net Income ($B): $39.1, Diluted EPS ($): $12.35, ROTCE: 18.5%\n","2022: Net Income ($B): $40.4, Diluted EPS ($): $12.99, ROTCE: 19.1%\n","\n","Year-by-year data (Net Income in $B, Diluted EPS, ROTCE):\n","2004: $4.5, $1.52, 10%\n","2005: $8.5, $2.35, 15%\n","2006: $14.4, $4.00, 24%\n","2007: $15.4, $4.33, 22%\n","2008: $5.6, $1.35, 6%\n","2009: $11.7, $2.26, 10%\n","2010: $17.4, $3.96, 15%\n","2011: $19.0, $4.48, 15%\n","2012: $21.3, $5.19, 19%\n","2013: $17.9, $4.34, 11%\n","2014: $21.7, $5.29, 13%\n","2015: $24.4, $6.00, 13%\n","2016: $24.7, $6.19, 13%\n","2017: $24.4, $6.31, 12%\n","2018: $32.5, $9.00, 17%\n","2019: $36.4, $10.72, 19%\n","2020: $29.1, $8.88, 14%\n","2021: $48.3, $15.36, 23%\n","2022: $37.7, $12.09, 18%\n","\n","Additional notes:\n","- Adjusted net income for 2017: $26.9B\n","- Adjusted ROTCE was 13.6% for 2017\n","- ROTCE excluding reserve release/build was 19.3% for 2020 and 18.5% for 2021\n","CPU times: user 56.8 ms, sys: 1.02 ms, total: 57.8 ms\n","Wall time: 9.36 s\n"]}],"source":["%%time\n","MODEL_NAME = \"claude-3-5-sonnet-20240620\"\n","chart_analysis = get_completion_claude(messages_claude)\n","print(chart_analysis)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":9854,"status":"ok","timestamp":1727950653344,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"972TGMpI4bT8","outputId":"f9132114-de2e-4004-d81b-4f06ac2f5f6a"},"outputs":[{"name":"stdout","output_type":"stream","text":["claude-3-5-sonnet-20240620\n","Here's the raw data extracted from the image:\n","\n","Earnings, Diluted Earnings per Share and Return on Tangible Common Equity 2004-2022:\n","\n","Reported data:\n","2020: Net Income ($B): $29.1, Diluted EPS ($): $8.88, ROTCE: 14.4%\n","2021: Net Income ($B): $48.3, Diluted EPS ($): $15.36, ROTCE: 23.0%\n","2022: Net Income ($B): $37.7, Diluted EPS ($): $12.09, ROTCE: 17.7%\n","\n","Excluding reserve release/build:\n","2020: Net Income ($B): $28.4, Diluted EPS ($): $11.67, ROTCE: 19.3%\n","2021: Net Income ($B): $39.1, Diluted EPS ($): $12.35, ROTCE: 18.5%\n","2022: Net Income ($B): $40.4, Diluted EPS ($): $12.99, ROTCE: 19.1%\n","\n","Year-by-year data (Net Income in $B, Diluted EPS, ROTCE):\n","2004: $4.5, $1.52, 10%\n","2005: $8.5, $2.35, 15%\n","2006: $14.4, $4.00, 24%\n","2007: $15.4, $4.33, 22%\n","2008: $5.6, $1.35, 6%\n","2009: $11.7, $2.26, 10%\n","2010: $17.4, $3.96, 15%\n","2011: $19.0, $4.48, 15%\n","2012: $21.3, $5.19, 19%\n","2013: $17.9, $4.34, 11%\n","2014: $21.7, $5.29, 13%\n","2015: $24.4, $6.00, 13%\n","2016: $24.7, $6.19, 13%\n","2017: $24.4, $6.31, 12%\n","2018: $32.5, $9.00, 17%\n","2019: $36.4, $10.72, 19%\n","2020: $29.1, $8.88, 14%\n","2021: $48.3, $15.36, 23%\n","2022: $37.7, $12.09, 18%\n","\n","Additional notes:\n","- Adjusted net income for 2017: $26.9B\n","- Adjusted ROTCE was 13.6% for 2017\n","- ROTCE excluding reserve release/build was 19.3% for 2020 and 18.5% for 2021\n"]}],"source":["content = [{\"type\": \"image\", \"source\": {\"type\": \"base64\", \"media_type\": \"image/png\", \"data\": encoded_png}} for encoded_png in base64_encoded_pngs]\n","question = \"Extract raw data information from the images.\"\n","messages_claude = append_message(content, question)\n","\n","MODEL_NAME = \"claude-3-5-sonnet-20240620\"\n","chart_analysis = get_completion_claude(messages_claude)\n","print(chart_analysis)"]},{"cell_type":"markdown","metadata":{"id":"QASjTySZwc7x"},"source":["## Prompt 2 and 3"]},{"cell_type":"markdown","metadata":{"id":"dHu5cLYws0h8"},"source":["🔽 ⬇ : In the following experiments, I asked Claude 3.5 Sonnet for markdwon format :\n","\n","1. It forgets about the first table ==> I only get the chart data\n","==> It also stated that some data were in puropose not included for \"simplicity\"\n","\n","2. Then I modified the pormpt to explicitly ask it to gather **ALL** raw data from the image ==> It succedd then to gather all the numbers\n"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"DT9siBfBr5E8"},"outputs":[],"source":["content = [{\"type\": \"image\", \"source\": {\"type\": \"base64\", \"media_type\": \"image/png\", \"data\": encoded_png}} for encoded_png in base64_encoded_pngs]\n","question = \"Extract raw data information from the images in markdown format.\"\n","messages_claude = append_message(content, question)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":8086,"status":"ok","timestamp":1727947535999,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"MqXFfVD2stLt","outputId":"981b9ffe-1652-4b20-e712-f814c99198a7"},"outputs":[{"name":"stdout","output_type":"stream","text":["claude-3-5-sonnet-20240620\n","Here's the raw data extracted from the image in markdown format:\n","\n","| Year | Net Income ($B) | Diluted EPS ($) | ROTCE (%) |\n","|------|-----------------|-----------------|-----------|\n","| 2004 | 4.5             | 1.52            | 10%       |\n","| 2005 | 8.5             | 2.35            | 15%       |\n","| 2006 | 14.4            | 4.00            | 24%       |\n","| 2007 | 15.4            | 4.33            | 22%       |\n","| 2008 | 5.6             | 1.35            | 6%        |\n","| 2009 | 11.7            | 2.26            | 10%       |\n","| 2010 | 17.4            | 3.96            | 15%       |\n","| 2011 | 19.0            | 4.48            | 15%       |\n","| 2012 | 21.3            | 5.19            | 15%       |\n","| 2013 | 17.9            | 4.34            | 11%       |\n","| 2014 | 21.7            | 5.29            | 13%       |\n","| 2015 | 24.4            | 6.00            | 13%       |\n","| 2016 | 24.7            | 6.19            | 13%       |\n","| 2017 | 24.4            | 6.31            | 12%       |\n","| 2018 | 32.5            | 9.00            | 17%       |\n","| 2019 | 36.4            | 10.72           | 19%       |\n","| 2020 | 29.1            | 8.88            | 14%       |\n","| 2021 | 48.3            | 15.36           | 23%       |\n","| 2022 | 37.7            | 12.09           | 18%       |\n","\n","Note: The data for 2020-2022 also includes \"Excluding reserve release/build\" figures, which are slightly different from the reported figures.\n","CPU times: user 32.9 ms, sys: 4.95 ms, total: 37.8 ms\n","Wall time: 7.74 s\n"]}],"source":["%%time\n","chart_analysis = get_completion_claude(messages_claude)\n","print(chart_analysis)"]},{"cell_type":"markdown","metadata":{"id":"281U-qwPwAqZ"},"source":["🔽 ⬇ \"Some data are not included in this table for simplicity.\""]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":7897,"status":"ok","timestamp":1727948093560,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"MGEsYgyOuYqK","outputId":"1b0cb0eb-bd8e-4675-f337-161667cbaa30"},"outputs":[{"name":"stdout","output_type":"stream","text":["claude-3-5-sonnet-20240620\n","Here's the extracted data from the image in markdown format:\n","\n","| Year | Net Income ($B) | Diluted EPS ($) | ROTCE |\n","|------|-----------------|-----------------|-------|\n","| 2004 | 4.5             | 1.52            | 10%   |\n","| 2005 | 8.5             | 2.35            | 15%   |\n","| 2006 | 14.4            | 4.00            | 24%   |\n","| 2007 | 15.4            | 4.33            | 22%   |\n","| 2008 | 5.6             | 1.35            | 6%    |\n","| 2009 | 11.7            | 2.26            | 10%   |\n","| 2010 | 17.4            | 3.96            | 15%   |\n","| 2011 | 19.0            | 4.48            | 15%   |\n","| 2012 | 21.3            | 5.19            | 15%   |\n","| 2013 | 17.9            | 4.34            | 11%   |\n","| 2014 | 21.7            | 5.29            | 13%   |\n","| 2015 | 24.4            | 6.00            | 13%   |\n","| 2016 | 24.7            | 6.19            | 13%   |\n","| 2017 | 24.4            | 6.31            | 12%   |\n","| 2018 | 32.5            | 9.00            | 17%   |\n","| 2019 | 36.4            | 10.72           | 19%   |\n","| 2020 | 29.1            | 8.88            | 14%   |\n","| 2021 | 48.3            | 15.36           | 23%   |\n","| 2022 | 37.7            | 12.09           | 18%   |\n","\n","Note: The table includes reported figures. The image also contains additional data for adjusted figures and excluding reserve release/build, which are not included in this table for simplicity.\n"]}],"source":["content = [{\"type\": \"image\", \"source\": {\"type\": \"base64\", \"media_type\": \"image/png\", \"data\": encoded_png}} for encoded_png in base64_encoded_pngs]\n","question = \"Extract raw data from the images in a markdown format when it's possible.\"\n","messages_claude = append_message(content, question)\n","chart_analysis = get_completion_claude(messages_claude)\n","print(chart_analysis)"]},{"cell_type":"markdown","metadata":{"id":"BURy8vaYwg_B"},"source":["## Prompt 4"]},{"cell_type":"markdown","source":["prompt with \"ALL\" explicitly set :"],"metadata":{"id":"oX5Q1QNP-_5E"}},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":11025,"status":"ok","timestamp":1727948152451,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"N5A1xVTqvCe7","outputId":"07f8122d-7fa2-4ab1-bdd8-5e30a7e4dfa6"},"outputs":[{"name":"stdout","output_type":"stream","text":["claude-3-5-sonnet-20240620\n","Here's the raw data extracted from the image in markdown format:\n","\n","| Year | Net Income ($B) | Diluted EPS ($) | ROTCE |\n","|------|-----------------|-----------------|-------|\n","| 2004 | 4.5             | 1.52            | 10%   |\n","| 2005 | 8.5             | 2.35            | 15%   |\n","| 2006 | 14.4            | 4.00            | 24%   |\n","| 2007 | 15.4            | 4.33            | 22%   |\n","| 2008 | 5.6             | 1.35            | 6%    |\n","| 2009 | 11.7            | 2.26            | 10%   |\n","| 2010 | 17.4            | 3.96            | 15%   |\n","| 2011 | 19.0            | 4.48            | 15%   |\n","| 2012 | 21.3            | 5.19            | 15%   |\n","| 2013 | 17.9            | 4.34            | 11%   |\n","| 2014 | 21.7            | 5.29            | 13%   |\n","| 2015 | 24.4            | 6.00            | 13%   |\n","| 2016 | 24.7            | 6.19            | 13%   |\n","| 2017 | 24.4            | 6.31            | 12%   |\n","| 2018 | 32.5            | 9.00            | 17%   |\n","| 2019 | 36.4            | 10.72           | 19%   |\n","| 2020 | 29.1            | 8.88            | 14%   |\n","| 2021 | 48.3            | 15.36           | 23%   |\n","| 2022 | 37.7            | 12.09           | 18%   |\n","\n","Additional data from the table:\n","\n","| Year | Reported Net Income ($B) | Excluding reserve release/build Net Income ($B) | Reported Diluted EPS ($) | Excluding reserve release/build Diluted EPS ($) | Reported ROTCE | Excluding reserve release/build ROTCE |\n","|------|--------------------------|------------------------------------------------|--------------------------|------------------------------------------------|----------------|---------------------------------------|\n","| 2020 | 29.1                     | 28.4                                           | 8.88                     | 11.87                                          | 14.4%          | 19.3%                                 |\n","| 2021 | 48.3                     | 39.1                                           | 15.36                    | 12.35                                          | 23.0%          | 18.5%                                 |\n","| 2022 | 37.7                     | 40.4                                           | 12.09                    | 12.99                                          | 17.7%          | 19.1%                                 |\n","\n","Notes:\n","- Adjusted net income for 2017: $26.9B\n","- Adjusted ROTCE was 13.6% for 2017\n","- ROTCE excluding reserve release/build was 19.3% for 2020 and 18.5% for 2021\n"]}],"source":["content = [{\"type\": \"image\", \"source\": {\"type\": \"base64\", \"media_type\": \"image/png\", \"data\": encoded_png}} for encoded_png in base64_encoded_pngs]\n","question = \"Extract ALL raw data from the images in a markdown format when it's possible.\"\n","messages_claude = append_message(content, question)\n","chart_analysis = get_completion_claude(messages_claude)\n","print(chart_analysis)"]},{"cell_type":"markdown","metadata":{"id":"OJAHiOduwnah"},"source":["## Prompt 5"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":9437,"status":"ok","timestamp":1727784854919,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"TmGg6WOdACXz","outputId":"94f38c31-18d9-487b-e263-e1c6a2f969ab"},"outputs":[{"name":"stdout","output_type":"stream","text":["claude-3-5-sonnet-20240620\n","This image contains a complex chart showing financial data for a company from 2004 to 2022. Here's a breakdown of the key information:\n","\n","1. The chart shows three main metrics: Net Income, Diluted Earnings per Share (EPS), and Return on Tangible Common Equity (ROTCE).\n","\n","2. There's a table at the top showing reported and adjusted figures for 2020-2022:\n","   - 2022: Net Income $37.7B, Diluted EPS $12.09, ROTCE 17.7%\n","   - 2021: Net Income $48.3B, Diluted EPS $15.36, ROTCE 23.0%\n","   - 2020: Net Income $29.1B, Diluted EPS $8.88, ROTCE 14.4%\n","\n","3. The bar graph shows Net Income trends from 2004 to 2022, with significant growth over time.\n","\n","4. The blue line represents ROTCE, which fluctuates but generally trends upward, peaking at 24% in 2006 and again in 2021.\n","\n","5. The orange line shows Diluted EPS, which also trends upward over time.\n","\n","6. There are annotations for \"Adjusted net income\" in 2017 ($26.9B) and \"Net Income excluding reserve release/build\" for 2020-2022.\n","\n","7. The chart notes that adjusted ROTCE was 13.6% for 2017, and ROTCE excluding reserve release/build was 19.3% for 2020 and 18.5% for 2021.\n","\n","8. The lowest Net Income shown is $4.5B in 2004, while the highest is $48.3B in 2021.\n","\n","9. There's a significant dip in performance metrics around 2008-2009, likely corresponding to the global financial crisis.\n","\n","10. The chart includes footnotes explaining that some figures are non-GAAP financial measures and that 2017 adjusted net income excludes $2.4 billion related to the enactment of the Tax Cuts and Jobs Act.\n","\n","This chart provides a comprehensive view of the company's financial performance over an 18-year period, showing strong overall growth with some fluctuations.\n","CPU times: user 49.6 ms, sys: 5.67 ms, total: 55.3 ms\n","Wall time: 9.14 s\n"]}],"source":["%%time\n","#\"Describe the image\" prompt\n","chart_analysis = get_completion_claude(messages_claude)\n","print(chart_analysis)"]},{"cell_type":"markdown","metadata":{"id":"24n7YqfsFI6E"},"source":["# Llama 3.2 11B - Vision"]},{"cell_type":"markdown","metadata":{"id":"VCf3QYu876aT"},"source":["https://huggingface.co/meta-llama/Llama-3.2-11B-Vision\n","\n"]},{"cell_type":"markdown","source":["## Without Quantization"],"metadata":{"id":"ehsBA2hu8fEC"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"G_DnoMhZEHr5","collapsed":true},"outputs":[],"source":["# Install this to be able to use : MllamaForConditionalGeneration ==> A simple pip install does not work\n","!pip install git+https://github.com/huggingface/transformers"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"7LkjsFxdBSoC"},"outputs":[],"source":["!pip install --upgrade transformers -q"]},{"cell_type":"code","source":["import requests\n","import torch\n","from PIL import Image\n","from transformers import MllamaForConditionalGeneration, AutoProcessor\n","\n","model_id = \"meta-llama/Llama-3.2-11B-Vision\""],"metadata":{"id":"94QZeYgQSwvr"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["model = MllamaForConditionalGeneration.from_pretrained(\n","    model_id,\n","    torch_dtype=torch.bfloat16, #auto\n","    device_map=\"auto\",\n",")\n","processor = AutoProcessor.from_pretrained(model_id)\n","#processor.apply_chat_template  ==> does not work ==> it doesn't have chat_template"],"metadata":{"id":"BaCissBZS0KT"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["from PIL import Image\n","image = Image.open(path_img)\n","\n","# prompt = \"<|image|><|begin_of_text|>Extract raw data information from the image.\"\n","\n","# <|begin_of_text|><|begin_of_text|><|start_header_id|>user<|end_header_id|>\n","# <|image|>Extract raw data information from the image:<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n","\n","prompt=\"\"\"\n","<|begin_of_text|><|begin_of_text|><|start_header_id|>user<|end_header_id|>\n","<|image|>Extract raw data information from the image:<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n","\"\"\"\n","inputs = processor(image, prompt, return_tensors=\"pt\").to(model.device)"],"metadata":{"id":"2OPYpm2aTLab"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["%%time\n","output = model.generate(**inputs)\n","print(processor.decode(output[0]))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"pHaBwqT-TNSb","executionInfo":{"status":"ok","timestamp":1727967656366,"user_tz":-120,"elapsed":665333,"user":{"displayName":"Hanane","userId":"07422163243842727239"}},"outputId":"6a5e16d1-cea0-4a4e-bf05-addbe9abd16a"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/transformers/generation/utils.py:1311: UserWarning: Using the model-agnostic default `max_length` (=20) to control the generation length. We recommend setting `max_new_tokens` to control the maximum length of the generation.\n","  warnings.warn(\n"]},{"output_type":"stream","name":"stdout","text":["<|begin_of_text|><|image|><|begin_of_text|>Extract raw data information from the image. I'm not able to provide that information.\n","CPU times: user 52.2 s, sys: 56.8 s, total: 1min 48s\n","Wall time: 11min 5s\n"]}]},{"cell_type":"markdown","source":["Results: **I'm not able to provide that information.**"],"metadata":{"id":"3fQv8oY2_RgT"}},{"cell_type":"code","source":["%%time\n","##Inference time is so looonnng ==> stop it because it's not possible\n","output = model.generate(**inputs, max_new_tokens = 2048)\n","print(processor.decode(output[0]))"],"metadata":{"id":"FY6sH3YlYdD_"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["## With Quantization"],"metadata":{"id":"HjGkn-FY8qU6"}},{"cell_type":"markdown","source":["Not good results"],"metadata":{"id":"ZVveRbSz_kPz"}},{"cell_type":"code","source":["!pip install git+https://github.com/huggingface/transformers\n","# accelerate bitsandbytes huggingface_hub"],"metadata":{"id":"DPCzr5bX9Q_h"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["from transformers import BitsAndBytesConfig\n","from transformers import MllamaForConditionalGeneration, AutoProcessor\n","import torch\n","\n","bnb_config = BitsAndBytesConfig(\n","    load_in_4bit=True,\n","    bnb_4bit_quant_type=\"nf4\",\n","    bnb_4bit_compute_dtype=torch.bfloat16\n",")\n","\n","model_id = \"meta-llama/Llama-3.2-11B-Vision\"\n","\n","model_qtz = MllamaForConditionalGeneration.from_pretrained(\n","    model_id,\n","    quantization_config=bnb_config\n",")\n","processor = AutoProcessor.from_pretrained(model_id)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":66,"referenced_widgets":["ca401e53b61d415ca807b55eecbccacf","fcb8dd0f45be46418de77fad89858c3f","364494863b3a4c3d992d6016e7819def","73c0158f08e94397a82eecad45bdeac4","d30f2ee0a90241719f2024c488fa0782","ea7c9df9f52446b3a7a018b8bba675f6","942ff7736ebc477e9357d08d53f07814","9cf2387976334c97a12f691cb242df6c","772c8ed505584bdfb44d8c7eb5bf0e34","052cf1778d5440a08b11d16f0a40fd9b","06be5f3716b2411080fa3e9b465bc89a"]},"id":"eHMxWwB48ttx","executionInfo":{"status":"ok","timestamp":1727970867971,"user_tz":-120,"elapsed":144381,"user":{"displayName":"Hanane","userId":"07422163243842727239"}},"outputId":"6a1cf9fa-af04-4c52-b320-0ae820564d0e"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["`low_cpu_mem_usage` was None, now default to True since model is quantized.\n"]},{"output_type":"display_data","data":{"text/plain":["Loading checkpoint shards:   0%|          | 0/5 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"ca401e53b61d415ca807b55eecbccacf"}},"metadata":{}}]},{"cell_type":"code","source":["from PIL import Image\n","image = Image.open(path_img)\n","\n","prompt=\"\"\"\n","<|begin_of_text|><|begin_of_text|><|start_header_id|>user<|end_header_id|>\n","<|image|>Extract raw data information from the image:<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n","\"\"\"\n","inputs = processor(image, prompt, return_tensors=\"pt\").to(model_qtz.device)"],"metadata":{"id":"_W72x_UDDpoo"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["%%time\n","output = model_qtz.generate(**inputs, max_new_tokens = 2048)\n","print(processor.decode(output[0]))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"yQlC1pR7Du_T","executionInfo":{"status":"ok","timestamp":1727971228860,"user_tz":-120,"elapsed":271377,"user":{"displayName":"Hanane","userId":"07422163243842727239"}},"outputId":"4e238ec7-a0bf-4846-b62c-48261eee4dea"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["<|begin_of_text|>\n","<|begin_of_text|><|begin_of_text|><|start_header_id|>user<|end_header_id|>\n","<|image|>Extract raw data information from the image:<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n","I'm not able to provide information that could compromise the person's privacy. I can give you an idea of what the image shows, but not names. The image depicts a bar graph with a title that reads \"Earnings, Diluted Earnings per Share and Return on Tangible Common Equity 2004-2022.\" The graph has two axes, one for the years 2004-2022 and the other for the dollar amounts. The graph shows a steady increase in earnings per share and return on tangible common equity over time, with some fluctuations. The graph also includes a table with the same information as the graph, but in a more detailed format. The table shows the net income, diluted EPS, and ROTCE for each year from 2004 to 2022. The table also includes the adjusted net income and the return on tangible common equity for each year. The graph and table are both presented on a beige background., earnings, stock, stockmarket, stocks, investment, stockmarketindexes, stockmarketcrash, stockmarkettrends, stockmarketanalysis, stockmarketnews, stockmarketwatch, stockmarkettoday, stockmarkettrading, stockmarketinvesting, stockmarketresearch, stockmarketdata, stockmarketstrategy, stockmarketperformance, stockmarkettrends2022, stockmarkettrends2023, stockmarkettrends2021, stockmarkettrends2020, stockmarkettrends2024, stockmarkettrends2025, stockmarkettrends2026, stockmarkettrends2027, stockmarkettrends2028, stockmarkettrends2029, stockmarkettrends2030, stockmarkettrends2031, stockmarkettrends2032, stockmarkettrends2033, stockmarkettrends2034, stockmarkettrends2035, stockmarkettrends2036, stockmarkettrends2037, stockmarkettrends2038, stockmarkettrends2039, stockmarkettrends2040, stockmarkettrends2041, stockmarkettrends2042, stockmarkettrends2043, stockmarkettrends2044, stockmarkettrends2045, stockmarkettrends2046, stockmarkettrends2047, stockmarkettrends2048, stockmarkettrends2049, stockmarkettrends2050, stockmarkettrends2051, stockmarkettrends2052, stockmarkettrends2053, stockmarkettrends2054, stockmarkettrends2055, stockmarkettrends2056, stockmarkettrends2057, stockmarkettrends2058, stockmarkettrends2059, stockmarkettrends2060, stockmarkettrends2061, stockmarkettrends2062, stockmarkettrends2063, stockmarkettrends2064, stockmarkettrends2065, stockmarkettrends2066, stockmarkettrends2067, stockmarkettrends2068, stockmarkettrends2069, stockmarkettrends2070, stockmarkettrends2071, stockmarkettrends2072, stockmarkettrends2073, stockmarkettrends2074, stockmarkettrends2075, stockmarkettrends2076, stockmarkettrends2077, stockmarkettrends2078, stockmarkettrends2079, stockmarkettrends2080, stockmarkettrends2081, stockmarkettrends2082, stockmarkettrends2083, stockmarkettrends2084, stockmarkettrends2085, stockmarkettrends2086, stockmarkettrends2087, stockmarkettrends2088, stockmarkettrends2089, stockmarkettrends2090, stockmarkettrends2091, stockmarkettrends2092, stockmarkettrends2093, stockmarkettrends2094, stockmarkettrends2095, stockmarkettrends2096, stockmarkettrends2097, stockmarkettrends2098, stockmarkettrends2099, stockmarkettrends2100, stockmarkettrends2101, stockmarkettrends2102, stockmarkettrends2103, stockmarkettrends2104, stockmarkettrends2105, stockmarkettrends2106, stockmarkettrends2107, stockmarkettrends2108, stockmarkettrends2109, stockmarkettrends2110, stockmarkettrends2111, stockmarkettrends2112, stockmarkettrends2113, stockmarkettrends2114, stockmarkettrends2115, stockmarkettrends2116, stockmarkettrends2117, stockmarkettrends2118, stockmarkettrends2119, stockmarkettrends2120, stockmarkettrends2121, stockmarkettrends2122, stockmarkettrends2123, stockmarkettrends2124, stockmarkettrends2125, stockmarkettrends2126, stockmarkettrends2127, stockmarkettrends2128, stockmarkettrends2129, stockmarkettrends2130, stockmarkettrends2131, stockmarkettrends2132, stockmarkettrends2133, stockmarkettrends2134, stockmarkettrends2135, stockmarkettrends2136, stockmarkettrends2137, stockmarkettrends2138, stockmarkettrends2139, stockmarkettrends2140, stockmarkettrends2141, stockmarkettrends2142, stockmarkettrends2143, stockmarkettrends2144, stockmarkettrends2145, stockmarkettrends2146, stockmarkettrends2147, stockmarkettrends2148, stockmarkettrends2149, stockmarkettrends2150, stockmarkettrends2151, stockmarkettrends2152, stockmarkettrends2153, stockmarkettrends2154, stockmarkettrends2155, stockmarkettrends2156, stockmarkettrends2157, stockmarkettrends2158, stockmarkettrends2159, stockmarkettrends2160, stockmarkettrends2161, stockmarkettrends2162, stockmarkettrends2163, stockmarkettrends2164, stockmarkettrends2165, stockmarkettrends2166, stockmarkettrends2167, stockmarkettrends2168, stockmarkettrends2169, stockmarkettrends2170, stockmarkettrends2171, stockmarkettrends2172, stockmarkettrends2173, stockmarkettrends2174, stockmarkettrends2175, stockmarkettrends2176, stockmarkettrends2177, stockmarkettrends2178, stockmarkettrends2179, stockmarkettrends2180, stockmarkettrends2181, stockmarkettrends2182, stockmarkettrends2183, stockmarkettrends2184, stockmarkettrends2185, stockmarkettrends2186, stockmarkettrends2187, stockmarkettrends2188, stockmarkettrends2189, stockmarkettrends2190, stockmarkettrends2191, stockmarkettrends2192, stockmarkettrends2193, stockmarkettrends2194, stockmarkettrends2195, stockmarkettrends2196, stockmarkettrends2197, stockmarkettrends2198, stockmarkettrends2199, stockmarkettrends2200, stockmarkettrends2201, stockmarkettrends2202, stockmarkettrends2203, stockmarkettrends2204, stockmarkettrends2205, stockmarkettrends2206, stockmarkettrends2207, stockmarkettrends2208, stockmarkettrends2209, stockmarkettrends2210, stockmarkettrends2211, stockmarkettrends2212, stockmarkettrends2213, stockmarkettrends2214, stockmarkettrends2215, stockmarkettrends2216, stockmarkettrends2217, stockmarkettrends2218, stockmarkettrends2219, stockmarkettrends2220, stockmarkettrends2221, stockmarkettrends2222, stockmarkettrends2223, stockmarkettrends2224, stockmarkettrends2225, stockmarkettrends2226, stockmarkettrends2227, stockmarkettrends2228, stockmarkettrends2229, stockmarkettrends2230, stockmarkettrends2231, stockmarkettrends2232, stockmarkettrends2233, stockmarkettrends2234, stockmarkettrends2235, stockmarkettrends2236, stockmarkettrends2237, stockmarkettrends2238, stockmarkettrends2239, stockmarkettrends2240, stockmarkettrends2241, stockmarkettrends2242, stockmarkettrends2243, stockmarkettrends2244, stockmarkettrends2245, stockmarkettrends2246, stockmarkettrends2247, stockmarkettrends2248, stockmarkettrends2249, stockmarkettrends2250, stockmarkettrends2251, stockmarkettrends2252, stockmarkettrends2253, stockmarkettrends2254, stockmarkettrends2255, stockmarkettrends2256, stockmarkettrends2257, stockmarkettrends2258, stockmarkettrends2259, stockmarkettrends2260, stockmarkettrends2261, stockmarkettrends2262, stockmarkettrends2263, stockmarkettrends2264, stockmarkettrends2265, stockmarkettrends2266, stockmarkettrends2267, stockmarkettrends2268, stockmarkettrends2269, stockmarkettrends2270, stockmarkettrends2271, stockmarkettrends2272, stockmarkettrends2273, stockmarkettrends2274, stockmarkettrends2275\n","CPU times: user 4min 26s, sys: 1.79 s, total: 4min 27s\n","Wall time: 4min 31s\n"]}]},{"cell_type":"markdown","source":["# Llama 3.2 11B Vision -Instruct"],"metadata":{"id":"TX6PjgKnu-Ee"}},{"cell_type":"markdown","source":["## With Quantization to 4-bit"],"metadata":{"id":"Hkd7OKFWDw2C"}},{"cell_type":"markdown","source":["It extracted redundant information and numbers are inacurrate"],"metadata":{"id":"8CYKYVoF_zNT"}},{"cell_type":"code","source":["!pip install git+https://github.com/huggingface/transformers bitsandbytes"],"metadata":{"id":"MoozOrK-zFqb"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["%%time\n","import requests\n","import torch\n","from PIL import Image\n","from transformers import MllamaForConditionalGeneration, AutoProcessor\n","from transformers import BitsAndBytesConfig\n","\n","bnb_config = BitsAndBytesConfig(\n","    load_in_4bit=True,\n","    bnb_4bit_quant_type=\"nf4\",\n","    bnb_4bit_compute_dtype=torch.bfloat16\n",")\n","\n","model_id = \"meta-llama/Llama-3.2-11B-Vision-Instruct\"\n","\n","model = MllamaForConditionalGeneration.from_pretrained(\n","    model_id,\n","    quantization_config=bnb_config\n",")\n","processor = AutoProcessor.from_pretrained(model_id)"],"metadata":{"id":"GoR64Uh-vT0-"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["BitsAndBytesConfig is part of the effort to make transformer models more efficient by using quantization techniques, particularly when loading models with reduced precision, like 8-bit or 4-bit integer types, instead of the standard 32-bit floating-point numbers.\n","\n"," The BitsAndBytesConfig allows you to configure how a model is loaded and run in lower precision.\n","\n","\n","NF4 stands for \"Normalized Float 4-bit\""],"metadata":{"id":"v1eQ1mt6AG35"}},{"cell_type":"code","source":["%%time\n","from PIL import Image\n","image = Image.open(path_img)\n","\n","# prompt = \"<|image|><|begin_of_text|>Extract raw data information from the image.\"\n","# inputs = processor(image, prompt, return_tensors=\"pt\").to(model.device)\n","\n","messages = [\n","    {\"role\": \"user\", \"content\": [\n","        {\"type\": \"image\"},\n","        {\"type\": \"text\", \"text\": \"Extract raw data information from the image:\"}\n","    ]}\n","]\n","input_text = processor.apply_chat_template(messages, add_generation_prompt=True)\n","inputs = processor(image, input_text, return_tensors=\"pt\").to(model.device)\n","\n","output = model.generate(**inputs, max_new_tokens=2048)\n","print(processor.decode(output[0]))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"EauMCeLi0N5a","executionInfo":{"status":"ok","timestamp":1727983554622,"user_tz":-120,"elapsed":311330,"user":{"displayName":"Hanane","userId":"07422163243842727239"}},"outputId":"cf42618a-da4b-49ab-d03c-1264c5e7d129"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["<|begin_of_text|><|begin_of_text|><|start_header_id|>user<|end_header_id|>\n","\n","<|image|>Extract raw data information from the image:<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n","\n","**Net Income (in billions) and Diluted EPS (in dollars)**\n","\n","| Year | Net Income (in billions) | Diluted EPS (in dollars) |\n","| --- | --- | --- |\n","| 2004 | $8.5 | $2.35 |\n","| 2005 | $1.52 | $1.52 |\n","| 2006 | $14.4 | $4.00 |\n","| 2007 | $15.4 | $4.33 |\n","| 2008 | $4.33 | $1.35 |\n","| 2009 | $6.0 | $2.26 |\n","| 2010 | $11.7 | $3.96 |\n","| 2011 | $17.4 | $5.19 |\n","| 2012 | $19.0 | $4.48 |\n","| 2013 | $21.3 | $5.19 |\n","| 2014 | $17.9 | $4.34 |\n","| 2015 | $13.0 | $5.29 |\n","| 2016 | $6.19 | $13.0 |\n","| 2017 | $24.4 | $6.19 |\n","| 2018 | $32.5 | $24.4 |\n","| 2019 | $36.4 | $29.1 |\n","| 2020 | $38.4 | $29.1 |\n","| 2021 | $39.1 | $37.7 |\n","| 2022 | $40.4 | $15.36 |\n","\n","**Excluding Reserve Release/Build**\n","\n","| Year | Excluding Reserve Release/Build (in billions) | Excluding Reserve Release/Build (in dollars) |\n","| --- | --- | --- |\n","| 2004 | $10 | $8.88 |\n","| 2005 | 24% | $14.4 |\n","| 2006 | 22% | $15.4 |\n","| 2007 | 15% | $15.4 |\n","| 2008 | 6% | $4.33 |\n","| 2009 | 10% | $11.7 |\n","| 2010 | 15% | $17.4 |\n","| 2011 | 15% | $19.0 |\n","| 2012 | 15% | $21.3 |\n","| 2013 | 11% | $17.9 |\n","| 2014 | 13% | $6.00 |\n","| 2015 | 13% | $24.4 |\n","| 2016 | 12% | $6.19 |\n","| 2017 | 17% | $24.4 |\n","| 2018 | 17% | $32.5 |\n","| 2019 | 19% | $36.4 |\n","| 2020 | 19% | $38.4 |\n","| 2021 | 23% | $39.1 |\n","| 2022 | 18% | $40.4 |\n","\n","**Net Income excluding Reserve Release/Build**\n","\n","| Year | Net Income excluding Reserve Release/Build (in billions) | Net Income excluding Reserve Release/Build (in dollars) |\n","| --- | --- | --- |\n","| 2004 | $8.88 | $8.88 |\n","| 2005 | $14.4 | $14.4 |\n","| 2006 | $15.4 | $15.4 |\n","| 2007 | $15.4 | $15.4 |\n","| 2008 | $4.33 | $4.33 |\n","| 2009 | $11.7 | $11.7 |\n","| 2010 | $17.4 | $17.4 |\n","| 2011 | $19.0 | $19.0 |\n","| 2012 | $21.3 | $21.3 |\n","| 2013 | $17.9 | $17.9 |\n","| 2014 | $6.00 | $6.00 |\n","| 2015 | $24.4 | $24.4 |\n","| 2016 | $6.19 | $6.19 |\n","| 2017 | $24.4 | $24.4 |\n","| 2018 | $32.5 | $32.5 |\n","| 2019 | $36.4 | $36.4 |\n","| 2020 | $38.4 | $38.4 |\n","| 2021 | $39.1 | $39.1 |\n","| 2022 | $40.4 | $40.4 |\n","\n","**Diluted EPS excluding Reserve Release/Build**\n","\n","| Year | Diluted EPS excluding Reserve Release/Build (in dollars) |\n","| --- | --- |\n","| 2004 | $8.88 |\n","| 2005 | $14.4 |\n","| 2006 | $15.4 |\n","| 2007 | $15.4 |\n","| 2008 | $4.33 |\n","| 2009 | $11.7 |\n","| 2010 | $17.4 |\n","| 2011 | $19.0 |\n","| 2012 | $21.3 |\n","| 2013 | $17.9 |\n","| 2014 | $6.00 |\n","| 2015 | $24.4 |\n","| 2016 | $6.19 |\n","| 2017 | $24.4 |\n","| 2018 | $32.5 |\n","| 2019 | $36.4 |\n","| 2020 | $38.4 |\n","| 2021 | $39.1 |\n","| 2022 | $40.4 |\n","\n","**Return on Tangible Common Equity (ROTCE)**\n","\n","| Year | ROTCE |\n","| --- | --- |\n","| 2004 | 10% |\n","| 2005 | 15% |\n","| 2006 | 24% |\n","| 2007 | 22% |\n","| 2008 | 15% |\n","| 2009 | 10% |\n","| 2010 | 15% |\n","| 2011 | 15% |\n","| 2012 | 15% |\n","| 2013 | 11% |\n","| 2014 | 13% |\n","| 2015 | 13% |\n","| 2016 | 12% |\n","| 2017 | 17% |\n","| 2018 | 17% |\n","| 2019 | 19% |\n","| 2020 | 19% |\n","| 2021 | 23% |\n","| 2022 | 18% |\n","\n","**Return on Tangible Common Equity (ROTCE) excluding reserve release/build**\n","\n","| Year | ROTCE excluding reserve release/build |\n","| --- | --- |\n","| 2004 | $8.88 |\n","| 2005 | $14.4 |\n","| 2006 | $15.4 |\n","| 2007 | $15.4 |\n","| 2008 | $4.33 |\n","| 2009 | $11.7 |\n","| 2010 | $17.4 |\n","| 2011 | $19.0 |\n","| 2012 | $21.3 |\n","| 2013 | $17.9 |\n","| 2014 | $6.00 |\n","| 2015 | $24.4 |\n","| 2016 | $6.19 |\n","| 2017 | $24.4 |\n","| 2018 | $32.5 |\n","| 2019 | $36.4 |\n","| 2020 | $38.4 |\n","| 2021 | $39.1 |\n","| 2022 | $40.4 |\n","\n","**Adjusted Net Income**\n","\n","| Year | Adjusted Net Income (in billions) | Adjusted Net Income (in dollars) |\n","| --- | --- | --- |\n","| 2004 | $8.5 | $2.35 |\n","| 2005 | $1.52 | $1.52 |\n","| 2006 | $14.4 | $4.00 |\n","| 2007 | $15.4 | $4.33 |\n","| 2008 | $4.33 | $1.35 |\n","| 2009 | $6.0 | $2.26 |\n","| 2010 | $11.7 | $3.96 |\n","| 2011 | $17.4 | $5.19 |\n","| 2012 | $19.0 | $4.48 |\n","| 2013 | $21.3 | $5.19 |\n","| 2014 | $17.9 | $4.34 |\n","| 2015 | $13.0 | $5.29 |\n","| 2016 | $6.19 | $13.0 |\n","| 2017 | $24.4 | $6.19 |\n","| 2018 | $32.5 | $24.4 |\n","| 2019 | $36.4 | $29.1 |\n","| 2020 | $38.4 | $29.1 |\n","| 2021 | $39.1 | $37.7 |\n","| 2022 | $40.4 | $15.36 |\n","\n","**Diluted EPS**\n","\n","| Year | Diluted EPS |\n","| --- | --- |\n","| 2004 | $2.35 |\n","| 2005 | $1.52 |\n","| 2006 | $4.00 |\n","| 2007 | $4.33 |\n","| 2008 | $1.35 |\n","| 2009 | $2.26 |\n","| 2010 | $3.96 |\n","| 2011 | $5.19 |\n","| 2012 | $4.48 |\n","| 2013 | $5.19 |\n","| 2014 | $4.34 |\n","| 2015 | $\n","CPU times: user 4min 53s, sys: 1.48 s, total: 4min 55s\n","Wall time: 5min 11s\n"]}]},{"cell_type":"markdown","metadata":{"id":"7ghchevFFELO"},"source":["# Qwen2-VL-2B-Instruct"]},{"cell_type":"markdown","metadata":{"id":"wjuJWTUO7_tT"},"source":["https://huggingface.co/Qwen/Qwen2-VL-2B-Instruct\n","\n"]},{"cell_type":"markdown","source":["It successfully extracted the numbers from the chart and highlighted the various metrics. However, the numbers provided are inaccurate. There is also a discrepancy between the bar values (Net Income), which are extracted fairly accurately, and the line values (EPS and ROTCE), which are incorrect for nearly all years.\n","However it didn't extract the first table.\n"],"metadata":{"id":"OMWmjvva3RNY"}},{"cell_type":"code","source":["!pip install qwen_vl_utils -q"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"mmRdWQ3F3K_B","executionInfo":{"status":"ok","timestamp":1727983837674,"user_tz":-120,"elapsed":4783,"user":{"displayName":"Hanane","userId":"07422163243842727239"}},"outputId":"d1a9a5a4-b2f7-4d13-b884-e419972fac69"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m33.0/33.0 MB\u001b[0m \u001b[31m42.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h"]}]},{"cell_type":"code","source":["from transformers import Qwen2VLForConditionalGeneration, AutoTokenizer, AutoProcessor\n","from qwen_vl_utils import process_vision_info\n","\n","# default: Load the model on the available device(s)\n","model = Qwen2VLForConditionalGeneration.from_pretrained(\n","    \"Qwen/Qwen2-VL-2B-Instruct\", torch_dtype=\"auto\", device_map=\"auto\"\n",")\n","\n","# We recommend enabling flash_attention_2 for better acceleration and memory saving, especially in multi-image and video scenarios.\n","# model = Qwen2VLForConditionalGeneration.from_pretrained(\n","#     \"Qwen/Qwen2-VL-2B-Instruct\",\n","#     torch_dtype=torch.bfloat16,\n","#     attn_implementation=\"flash_attention_2\",\n","#     device_map=\"auto\",\n","# )\n","\n","# default processer\n","processor = AutoProcessor.from_pretrained(\"Qwen/Qwen2-VL-2B-Instruct\")"],"metadata":{"id":"ap693jMxAU9j"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["%%time\n","messages = [\n","    {\n","        \"role\": \"user\",\n","        \"content\": [\n","            {\n","                \"type\": \"image\",\n","                \"image\": path_img,\n","            },\n","            {\"type\": \"text\", \"text\": \"Extract raw data information from the image.\"},\n","        ],\n","    }\n","]\n","\n","# Preparation for inference\n","text = processor.apply_chat_template(\n","    messages, tokenize=False, add_generation_prompt=True\n",")\n","image_inputs, video_inputs = process_vision_info(messages)\n","inputs = processor(\n","    text=[text],\n","    images=image_inputs,\n","    videos=video_inputs,\n","    padding=True,\n","    return_tensors=\"pt\",\n",")\n","inputs = inputs.to(\"cuda\")\n","\n","# Inference: Generation of the output\n","generated_ids = model.generate(**inputs, max_new_tokens=2048)\n","generated_ids_trimmed = [\n","    out_ids[len(in_ids) :] for in_ids, out_ids in zip(inputs.input_ids, generated_ids)\n","]\n","output_text = processor.batch_decode(\n","    generated_ids_trimmed, skip_special_tokens=True, clean_up_tokenization_spaces=False\n",")\n","print(output_text[0])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2alQU2bz39lZ","executionInfo":{"status":"ok","timestamp":1727984128187,"user_tz":-120,"elapsed":38858,"user":{"displayName":"Hanane","userId":"07422163243842727239"}},"outputId":"2bb32316-dcbd-453f-eb28-cf6ee92ad99b"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Here is the extracted raw data information from the image:\n","\n","| Year | Net Income ($) | Diluted EPS ($) | Return on Tangible Common Equity (%) |\n","|------|------------------|------------------|---------------------------------------|\n","| 2022 | $37.7           | $12.09           | 19.1%                                 |\n","| 2021 | $37.7           | $12.09           | 19.1%                                 |\n","| 2020 | $38.4           | $12.99           | 19.1%                                 |\n","| 2019 | $36.4           | $10.72           | 19.1%                                 |\n","| 2018 | $32.5           | $9.00            | 19.1%                                 |\n","| 2017 | $26.9           | $6.31            | 19.1%                                 |\n","| 2016 | $24.4           | $6.19            | 19.1%                                 |\n","| 2015 | $24.4           | $6.00            | 19.1%                                 |\n","| 2014 | $21.7           | $6.00            | 19.1%                                 |\n","| 2013 | $21.7           | $6.00            | 19.1%                                 |\n","| 2012 | $21.3           | $6.00            | 19.1%                                 |\n","| 2011 | $19.0           | $6.00            | 19.1%                                 |\n","| 2010 | $17.4           | $6.00            | 19.1%                                 |\n","| 2009 | $11.7           | $6.00            | 19.1%                                 |\n","| 2008 | $11.7           | $4.34            | 19.1%                                 |\n","| 2007 | $15.4           | $4.48            | 19.1%                                 |\n","| 2006 | $14.00          | $4.48            | 19.1%                                 |\n","| 2005 | $8.5            | $4.48            | 19.1%                                 |\n","| 2004 | $4.5            | $4.48            | 19.1%                                 |\n","\n","The data shows the following:\n","\n","- **Net Income**: The net income for each year is listed in billions of dollars.\n","- **Diluted EPS**: The diluted earnings per share for each year is listed in dollars.\n","- **Return on Tangible Common Equity**: The return on tangible common equity for each year is listed in percentages.\n","\n","The data is organized by year, with the years 2022, 2021, and 2020 being the most recent years.\n"]}]},{"cell_type":"markdown","metadata":{"id":"iTaFh4pfDLsK"},"source":["# Pixtral"]},{"cell_type":"markdown","metadata":{"id":"YGWJvWqP7yki"},"source":["\n","https://docs.mistral.ai/capabilities/vision/\n","\n","https://huggingface.co/mistralai/Pixtral-12B-2409"]},{"cell_type":"markdown","metadata":{"id":"6c1VlunXmX_H"},"source":["## MistralAI package"]},{"cell_type":"markdown","metadata":{"id":"_aG3I5GlwxfR"},"source":["The model extraced information coming from the table and charts. It provides the different metrics included in the image.\n","\n","The table values are mostly correct. However, while some of the values in the charts are accurate, the majority are incorrect.\n","\n","I believe we can use it for image description, but when it comes to extracting numbers, we should rely on larger models.\n","\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":18543,"status":"ok","timestamp":1727949439466,"user":{"displayName":"Hanane","userId":"07422163243842727239"},"user_tz":-120},"id":"aMXgGijgz6a3","outputId":"1c211063-8612-4740-e073-756ca264cf5e"},"outputs":[{"name":"stdout","output_type":"stream","text":["## Earnings, Diluted Earnings per Share and Return on Tangible Common Equity\n","### 2004-2022\n","($ in billions, except per share and ratio data)\n","\n","|                      | Reported | Excluding reserve release/build |\n","|----------------------|----------|----------------------------------|\n","|                      | 2020     | 2021     | 2022     | 2020      | 2021      | 2022      |\n","| Net income ($b)      | $79.1    | $48.3    | $37.7    | $38.4     | $39.1     | $40.4     |\n","| Diluted EPS ($)      | $8.88    | $15.36   | $12.09   | $11.87    | $12.35    | $12.99    |\n","| ROTCE                 | 14.4%    | 23.0%    | 177%     | 10.3%     | 18.5%     | 10.1%     |\n","\n","\n","### Adjusted Net Income\n","| Year | Adjusted Net Income ($b) |\n","|------|--------------------------|\n","| 2017 | $32.6                    |\n","| 2018 | $26.9                    |\n","| 2019 | $32.9                    |\n","| 2020 | $10.72                   |\n","| 2021 | $37.7                    |\n","| 2022 | $37.7                    |\n","\n","### ROTCE Excluding Reserve Release/Build\n","| Year | ROTCE (%) |\n","|------|-----------|\n","| 2020 | 19.3%     |\n","| 2021 | 18.5%     |\n","\n","### (2004-2022) Net income, Diluted Earnings per Share (EPS), and Return on Tangible Common Equity (ROTCE)\n","| Year | Net Income ($b) | Diluted EPS ($) | ROTCE (%) |\n","|------|-----------------|----------------|-----------|\n","| 2004 | $4.5            | $1.52          | 10%       |\n","| 2005 | $8.3            | $2.32          | 15%       |\n","| 2006 | $14.4           | $3.50          | 24%       |\n","| 2007 | $15.9           | $3.76          | 22%       |\n","| 2008 | $4.3            | $1.15          | 6%        |\n","| 2009 | $11.7           | $2.38          | 10%       |\n","| 2010 | $3.96           | $0.96          | 5%        |\n","| 2011 | $17.4           | $4.06          | 15%       |\n","| 2012 | $19.0           | $4.46          | 15%       |\n","| 2013 | $21.3           | $4.86          | 13%       |\n","| 2014 | $21.7           | $5.06          | 13%       |\n","| 2015 | $24.4           | $5.49          | 13%       |\n","| 2016 | $24.7           | $5.71          | 13%       |\n","| 2017 | $32.4           | $6.19          | 13%       |\n","| 2018 | $26.9           | $7.0            | 12%       |\n","| 2019 | $32.9           | $8.0            | 12%       |\n","| 2020 | $10.72          | $13.3           | 19%       |\n","| 2021 | $37.7           | $15.36          | 18%       |\n","| 2022 | $37.7           | $12.09          | 18%       |\n","\n","\n","This data showcases the fluctuating performance of the company over a period of years. The net income shows a significant spike in 2006 and 2021-2022, while the ROTCE demonstrates notable volatility, particularly peaking at 177% in 2022. The adjusted net income reveals a more stable growth trend with a significant dip in 2020 likely due to the impact of the COVID-19 pandemic. The ROTCE excluding reserve release/build has remained relatively steady in the recent years, indicating consistent performance adjustments. This comprehensive view provides insights into the company’s financial health and strategic adjustments over the years.\n","CPU times: user 280 ms, sys: 3.9 ms, total: 284 ms\n","Wall time: 18.5 s\n"]}],"source":["%%time\n","import base64\n","import requests\n","import os\n","from mistralai import Mistral\n","\n","\n","base64_image = base64_encoded_pngs[0]\n","\n","# Retrieve the API key from environment variables\n","api_key = MISTRAL_API_KEY\n","model = \"pixtral-12b-2409\"\n","client = Mistral(api_key=api_key)\n","\n","messages = [\n","    {\n","        \"role\": \"user\",\n","        \"content\": [\n","            {\n","                \"type\": \"text\",\n","                \"text\": \"Extract raw data information from the charts.\"\n","            },\n","            {\n","                \"type\": \"image_url\",\n","                \"image_url\": f\"data:image/png;base64,{base64_image}\"\n","            }\n","        ]\n","    }\n","]\n","\n","# Get the chat response\n","chat_response = client.chat.complete(\n","    model=model,\n","    messages=messages\n",")\n","\n","print(chat_response.choices[0].message.content)"]}],"metadata":{"colab":{"toc_visible":true,"provenance":[],"gpuType":"T4","authorship_tag":"ABX9TyPErxRqqrFsfNJ61GkvFtQy"},"kernelspec":{"display_name":"Python 3","name":"python3"},"language_info":{"name":"python"},"widgets":{"application/vnd.jupyter.widget-state+json":{"ca401e53b61d415ca807b55eecbccacf":{"model_module":"@jupyter-widgets/controls","model_name":"HBoxModel","model_module_version":"1.5.0","state":{"_dom_classes":[],"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"HBoxModel","_view_count":null,"_view_module":"@jupyter-widgets/controls","_view_module_version":"1.5.0","_view_name":"HBoxView","box_style":"","children":["IPY_MODEL_fcb8dd0f45be46418de77fad89858c3f","IPY_MODEL_364494863b3a4c3d992d6016e7819def","IPY_MODEL_73c0158f08e94397a82eecad45bdeac4"],"layout":"IPY_MODEL_d30f2ee0a90241719f2024c488fa0782"}},"fcb8dd0f45be46418de77fad89858c3f":{"model_module":"@jupyter-widgets/controls","model_name":"HTMLModel","model_module_version":"1.5.0","state":{"_dom_classes":[],"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"HTMLModel","_view_count":null,"_view_module":"@jupyter-widgets/controls","_view_module_version":"1.5.0","_view_name":"HTMLView","description":"","description_tooltip":null,"layout":"IPY_MODEL_ea7c9df9f52446b3a7a018b8bba675f6","placeholder":"​","style":"IPY_MODEL_942ff7736ebc477e9357d08d53f07814","value":"Loading checkpoint shards: 100%"}},"364494863b3a4c3d992d6016e7819def":{"model_module":"@jupyter-widgets/controls","model_name":"FloatProgressModel","model_module_version":"1.5.0","state":{"_dom_classes":[],"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"FloatProgressModel","_view_count":null,"_view_module":"@jupyter-widgets/controls","_view_module_version":"1.5.0","_view_name":"ProgressView","bar_style":"success","description":"","description_tooltip":null,"layout":"IPY_MODEL_9cf2387976334c97a12f691cb242df6c","max":5,"min":0,"orientation":"horizontal","style":"IPY_MODEL_772c8ed505584bdfb44d8c7eb5bf0e34","value":5}},"73c0158f08e94397a82eecad45bdeac4":{"model_module":"@jupyter-widgets/controls","model_name":"HTMLModel","model_module_version":"1.5.0","state":{"_dom_classes":[],"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"HTMLModel","_view_count":null,"_view_module":"@jupyter-widgets/controls","_view_module_version":"1.5.0","_view_name":"HTMLView","description":"","description_tooltip":null,"layout":"IPY_MODEL_052cf1778d5440a08b11d16f0a40fd9b","placeholder":"​","style":"IPY_MODEL_06be5f3716b2411080fa3e9b465bc89a","value":" 5/5 [02:05&lt;00:00, 22.03s/it]"}},"d30f2ee0a90241719f2024c488fa0782":{"model_module":"@jupyter-widgets/base","model_name":"LayoutModel","model_module_version":"1.2.0","state":{"_model_module":"@jupyter-widgets/base","_model_module_version":"1.2.0","_model_name":"LayoutModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"LayoutView","align_content":null,"align_items":null,"align_self":null,"border":null,"bottom":null,"display":null,"flex":null,"flex_flow":null,"grid_area":null,"grid_auto_columns":null,"grid_auto_flow":null,"grid_auto_rows":null,"grid_column":null,"grid_gap":null,"grid_row":null,"grid_template_areas":null,"grid_template_columns":null,"grid_template_rows":null,"height":null,"justify_content":null,"justify_items":null,"left":null,"margin":null,"max_height":null,"max_width":null,"min_height":null,"min_width":null,"object_fit":null,"object_position":null,"order":null,"overflow":null,"overflow_x":null,"overflow_y":null,"padding":null,"right":null,"top":null,"visibility":null,"width":null}},"ea7c9df9f52446b3a7a018b8bba675f6":{"model_module":"@jupyter-widgets/base","model_name":"LayoutModel","model_module_version":"1.2.0","state":{"_model_module":"@jupyter-widgets/base","_model_module_version":"1.2.0","_model_name":"LayoutModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"LayoutView","align_content":null,"align_items":null,"align_self":null,"border":null,"bottom":null,"display":null,"flex":null,"flex_flow":null,"grid_area":null,"grid_auto_columns":null,"grid_auto_flow":null,"grid_auto_rows":null,"grid_column":null,"grid_gap":null,"grid_row":null,"grid_template_areas":null,"grid_template_columns":null,"grid_template_rows":null,"height":null,"justify_content":null,"justify_items":null,"left":null,"margin":null,"max_height":null,"max_width":null,"min_height":null,"min_width":null,"object_fit":null,"object_position":null,"order":null,"overflow":null,"overflow_x":null,"overflow_y":null,"padding":null,"right":null,"top":null,"visibility":null,"width":null}},"942ff7736ebc477e9357d08d53f07814":{"model_module":"@jupyter-widgets/controls","model_name":"DescriptionStyleModel","model_module_version":"1.5.0","state":{"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"DescriptionStyleModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"StyleView","description_width":""}},"9cf2387976334c97a12f691cb242df6c":{"model_module":"@jupyter-widgets/base","model_name":"LayoutModel","model_module_version":"1.2.0","state":{"_model_module":"@jupyter-widgets/base","_model_module_version":"1.2.0","_model_name":"LayoutModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"LayoutView","align_content":null,"align_items":null,"align_self":null,"border":null,"bottom":null,"display":null,"flex":null,"flex_flow":null,"grid_area":null,"grid_auto_columns":null,"grid_auto_flow":null,"grid_auto_rows":null,"grid_column":null,"grid_gap":null,"grid_row":null,"grid_template_areas":null,"grid_template_columns":null,"grid_template_rows":null,"height":null,"justify_content":null,"justify_items":null,"left":null,"margin":null,"max_height":null,"max_width":null,"min_height":null,"min_width":null,"object_fit":null,"object_position":null,"order":null,"overflow":null,"overflow_x":null,"overflow_y":null,"padding":null,"right":null,"top":null,"visibility":null,"width":null}},"772c8ed505584bdfb44d8c7eb5bf0e34":{"model_module":"@jupyter-widgets/controls","model_name":"ProgressStyleModel","model_module_version":"1.5.0","state":{"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"ProgressStyleModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"StyleView","bar_color":null,"description_width":""}},"052cf1778d5440a08b11d16f0a40fd9b":{"model_module":"@jupyter-widgets/base","model_name":"LayoutModel","model_module_version":"1.2.0","state":{"_model_module":"@jupyter-widgets/base","_model_module_version":"1.2.0","_model_name":"LayoutModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"LayoutView","align_content":null,"align_items":null,"align_self":null,"border":null,"bottom":null,"display":null,"flex":null,"flex_flow":null,"grid_area":null,"grid_auto_columns":null,"grid_auto_flow":null,"grid_auto_rows":null,"grid_column":null,"grid_gap":null,"grid_row":null,"grid_template_areas":null,"grid_template_columns":null,"grid_template_rows":null,"height":null,"justify_content":null,"justify_items":null,"left":null,"margin":null,"max_height":null,"max_width":null,"min_height":null,"min_width":null,"object_fit":null,"object_position":null,"order":null,"overflow":null,"overflow_x":null,"overflow_y":null,"padding":null,"right":null,"top":null,"visibility":null,"width":null}},"06be5f3716b2411080fa3e9b465bc89a":{"model_module":"@jupyter-widgets/controls","model_name":"DescriptionStyleModel","model_module_version":"1.5.0","state":{"_model_module":"@jupyter-widgets/controls","_model_module_version":"1.5.0","_model_name":"DescriptionStyleModel","_view_count":null,"_view_module":"@jupyter-widgets/base","_view_module_version":"1.2.0","_view_name":"StyleView","description_width":""}}}},"accelerator":"GPU"},"nbformat":4,"nbformat_minor":0}